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Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3, Qwen3-MoE, DeepSeek-R1, GLM4.5, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM4.5v, Llava, …
gpt-oss-120b and gpt-oss-20b are two open-weight language models by OpenAI
Implementation of "Multi-modal Retrieval Augmented Multi-modal Generation: Datasets, Evaluation Metrics and Strong Baselines"
This repository contains the Hugging Face Agents Course.
A fork to add multimodal model training to open-r1
Grokking the Coding Interview: Patterns for Coding Questions Alternative
The simplest, fastest repository for training/finetuning medium-sized GPTs.
A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆26 knowledge distillation methods presented at TPAMI, CVPR, ICLR, ECCV, NeurIPS, ICCV, AAAI, etc…
An official repository for MIA 2022 (NAACL 2022 Workshop) Shared Task on Cross-lingual Open-Retrieval Question Answering.
Neural Machine Translation on the Nepali-English language pair
Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative ski…
Parameterized Explainer for Graph Neural Network
SparseMax activation function implementation (ICML 2016) (PyTorch)
From Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)
A simple way to calibrate your neural network.
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
All the ML algorithms, ML models are coded from scratch by pure Python/Numpy with the Math under the hood. It works well on CPU.
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.
Collection of probabilistic models and inference algorithms
Listing of papers about machine learning for proteins.
Topics course Mathematics of Deep Learning, NYU, Spring 18
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